1. Technical Field
The present invention relates generally to sub-iteration contexts in a transformation operation in a data integration system, and more particularly to systems and methods for the derivation and application of sub-iteration contexts to provide meaningful target data in a transformation operation in a data integration system.
2. Discussion of Related Art
Data integration systems such as ETL systems (e.g. IBM InfoSphere DataStage) and data mashup systems (e.g. IBM InfoSphere MashupHub) commonly provide transformation operators (e.g. the Transform or Extract operators of InfoSphere MashupHub Version 2.0) that perform a transformation operation wherein source data is transformed from one format and structure to another. Such transformation operations often involve the creation of elements and attributes whose structure and content are derived from expressions involving repeating elements of the source data. In order to create the necessary elements and attributes, the user must be both technically knowledgeable and have detailed knowledge about the incoming data, which is very difficult in the context of a data mashup system because the data is coming from a variety of dynamic, external sources pulled from around the Web.
As an example, a user of a data mashup system might wish to perform a “transformation operation” that converts a source feed containing repeating elements into a target feed. In order to handle the transformation of the repeating elements, current data integration systems and tools require explicit specification of sub-iteration points in the definition of a transformation operation. For example, a transformation operation might be specified in full programmatic detail using languages such as XQuery or XSLT.
Data integration tools such as Clio improve upon this approach by allowing a transformation operation to be programmed graphically through specification of associations between a source schema and target schema. These schemas represent, respectively, the format and structure of all possible source and target instance data; consequently, the user must understand the structure of all possible source and target data instances in order to design correct source and target schemas. In particular, the user must understand the repeating properties of the data in order to correctly specify the repeating attributes of schema elements (e.g. the “minoccurs” and “maxoccurs” attributes in Xschema).